Author: Uri Blass
Date: 23:34:22 12/24/02
Go up one level in this thread
On December 24, 2002 at 23:05:09, Robert Hyatt wrote: >On December 24, 2002 at 19:24:04, Vincent Diepeveen wrote: > >>On December 23, 2002 at 19:21:57, Uri Blass wrote: >> >>>On December 23, 2002 at 18:31:03, Dieter Buerssner wrote: >>> >>>>On December 23, 2002 at 18:08:15, Martin Bauer wrote: >>>> >>>>>Hello, >>>>> >>>>>i have a queastion about move ordering. There are many sources with move >>>>>ordering heuristics like killer heuristic, history and so on... >>>>> >>>>>But I found no description _how_ to program the move ordering in an _efficient_ >>>>>way. In my own enginge I use an integer value together with the move and put it >>>>>on the move stack. Moves that should be searched first, become a high value and >>>>>the less important moves a low one. Then there is a function named >>>>>"NextBestMove" that that looks for the highest value at the actual searchdepth >>>>>on the movestack. Therefore it must look at all possible moves in the actual >>>>>position. When the best move is found, the value is set to -Matescore, so it can >>>>>not get the best move the next time the function is called. >>>> >>>>This is the normal way to do it, I think. Instead of giving a "marker score", to >>>>not search the move again, you could shift the move to the start or to the end >>>>of the array, and remember the new bounds (incrementing a pointer may be enough >>>>for this). This will save a few CPU cycles. It is essentially the inner loop of >>>>a normal selection sort. >>>> >>>>>This algorithm must have a look at all possible moves in the position at the >>>>>actual depth, even if the frist 10 best moves are searched. This look not >>>>>efficient to me, because it is an O(n) algorithm in reading the best move and >>>>>O(1) in storing the best move. >>>> >>>>I think, there is no practical better way. Sorting the whole move list can >>>>easily be done faster (especially, when it has some considerable length, so not >>>>just relpy to check). But often, the work will be done for nothing, because one >>>>move will be enough for a cutoff. I experimented a bit with the following idea: >>>>Try to guess, when we expect a fail high node: use the selection sort method >>>>above. Whe expecting a fail low node, do a qsort (the Standard C-language qsort >>>>would probably be a bit slow for this, because of all the calls to the compare >>>>function, I had written my own). But, I really could not measure any performance >>>>increase, so I gave up on the idea. It just made the code bigger ... >>> >>>If you expect a fail low move you can simply not care about order of moves. >> >>This is utter nonsense. >> >>==> note that it is another years 80 design issue in crafty >> >>For many reasons sorting is better. To just list a few >> a) it *might* give a cutoff now. No heuristic is 100% accurate >> going to predict it is going to get a fail low again. >> The proof for that is obvious. If you know it for 100% sure you >> can simply return alpha and stop searching this node! >> b) it goes into hashtable and gets reused later. You perhaps do not >> expect a fail low then but the best move saved in the hashtable is >> a random move in your case >> c) it improves positional play obviously. Suppose you pick a random >> move giving 0.001 versus a chosen move 0.001. The chosen move on >> average is better. Do not underestimate this effect at all. this is >> not a 'once in a million moves i play' scenario. > >That is utter clap-trap. Why don't you go read Knuth/Moore's paper on >alpha beta. There you will find that move ordering does _not_ affect the >final score, only the size of the tree. Something every senion-level computer >science student should know. I can imagine a case that it can affect the final score. Suppose that there are 2 moves that potentialy gives fail high that you did not search move A and move B. if you search first move A you get a score for move A and move B is pruned by null move pruning. if you search first move B then move B is not pruned by null move pruning and you get a bigger score for move B so you do not play move A. It does not mean that not sorting is a mistake because being faster is an advantage and I do not think that the quality of order by history table is good in any case so not sorting after enough moves is an advantage for a lot of programs. Uri
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